Overview

Dataset statistics

Number of variables17
Number of observations109020
Missing cells44386
Missing cells (%)2.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.1 MiB
Average record size in memory136.0 B

Variable types

Numeric5
Text8
Categorical3
DateTime1

Alerts

Latitude is highly overall correlated with StateHigh correlation
Longitude is highly overall correlated with StateHigh correlation
State is highly overall correlated with Latitude and 1 other fieldsHigh correlation
State is highly imbalanced (99.9%)Imbalance
Facility Type has 1667 (1.5%) missing valuesMissing
Violations has 40526 (37.2%) missing valuesMissing
Zip is highly skewed (γ1 = -72.30505907)Skewed
Inspection ID has unique valuesUnique

Reproduction

Analysis started2024-02-15 22:29:51.152152
Analysis finished2024-02-15 22:30:56.446482
Duration1 minute and 5.29 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

Inspection ID
Real number (ℝ)

UNIQUE 

Distinct109020
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2218833.6
Minimum44255
Maximum2589384
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size851.8 KiB
2024-02-15T22:30:56.628212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum44255
5-th percentile670471.6
Q12222462.8
median2373464.5
Q32557003.2
95-th percentile2583318
Maximum2589384
Range2545129
Interquartile range (IQR)334540.5

Descriptive statistics

Standard deviation539887.33
Coefficient of variation (CV)0.24332034
Kurtosis4.5164173
Mean2218833.6
Median Absolute Deviation (MAD)181312
Skewness-2.2418915
Sum2.4189723 × 1011
Variance2.9147833 × 1011
MonotonicityNot monotonic
2024-02-15T22:30:56.950025image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2589380 1
 
< 0.1%
2484494 1
 
< 0.1%
2456923 1
 
< 0.1%
2472308 1
 
< 0.1%
2472812 1
 
< 0.1%
2463593 1
 
< 0.1%
2472815 1
 
< 0.1%
2492602 1
 
< 0.1%
2493183 1
 
< 0.1%
2492394 1
 
< 0.1%
Other values (109010) 109010
> 99.9%
ValueCountFrequency (%)
44255 1
< 0.1%
48219 1
< 0.1%
48220 1
< 0.1%
48221 1
< 0.1%
48223 1
< 0.1%
52241 1
< 0.1%
52253 1
< 0.1%
52258 1
< 0.1%
52261 1
< 0.1%
54225 1
< 0.1%
ValueCountFrequency (%)
2589384 1
< 0.1%
2589383 1
< 0.1%
2589380 1
< 0.1%
2589377 1
< 0.1%
2589376 1
< 0.1%
2589375 1
< 0.1%
2589373 1
< 0.1%
2589370 1
< 0.1%
2589369 1
< 0.1%
2589362 1
< 0.1%
Distinct23936
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size851.8 KiB
2024-02-15T22:30:57.502415image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length79
Median length47
Mean length18.75599
Min length1

Characters and Unicode

Total characters2044778
Distinct characters84
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7116 ?
Unique (%)6.5%

Sample

1st rowE Z MARKET, INC.
2nd rowJOHNNIE'S PIZZA
3rd rowDivan Chicago
4th rowSUBWAY
5th rowBurke
ValueCountFrequency (%)
10136
 
3.1%
inc 10115
 
3.1%
restaurant 5659
 
1.7%
the 4695
 
1.4%
food 4194
 
1.3%
cafe 3571
 
1.1%
chicago 3517
 
1.1%
llc 3332
 
1.0%
grill 2912
 
0.9%
and 2897
 
0.9%
Other values (15617) 280444
84.6%
2024-02-15T22:30:58.668175image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
224210
 
11.0%
A 168937
 
8.3%
E 167836
 
8.2%
R 120881
 
5.9%
I 118880
 
5.8%
O 118820
 
5.8%
N 112975
 
5.5%
S 111772
 
5.5%
T 101530
 
5.0%
C 96556
 
4.7%
Other values (74) 702381
34.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1664339
81.4%
Space Separator 224210
 
11.0%
Lowercase Letter 71210
 
3.5%
Other Punctuation 49685
 
2.4%
Decimal Number 30209
 
1.5%
Dash Punctuation 3703
 
0.2%
Open Punctuation 603
 
< 0.1%
Close Punctuation 603
 
< 0.1%
Math Symbol 208
 
< 0.1%
Modifier Symbol 3
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 168937
 
10.2%
E 167836
 
10.1%
R 120881
 
7.3%
I 118880
 
7.1%
O 118820
 
7.1%
N 112975
 
6.8%
S 111772
 
6.7%
T 101530
 
6.1%
C 96556
 
5.8%
L 90466
 
5.4%
Other values (16) 455686
27.4%
Lowercase Letter
ValueCountFrequency (%)
e 8788
12.3%
a 7540
10.6%
o 6203
 
8.7%
n 5789
 
8.1%
r 5606
 
7.9%
i 4930
 
6.9%
t 4454
 
6.3%
l 4413
 
6.2%
s 3697
 
5.2%
c 2901
 
4.1%
Other values (16) 16889
23.7%
Other Punctuation
ValueCountFrequency (%)
' 16338
32.9%
. 9461
19.0%
& 8177
16.5%
, 6941
14.0%
# 5934
 
11.9%
/ 2233
 
4.5%
@ 402
 
0.8%
! 138
 
0.3%
? 29
 
0.1%
: 13
 
< 0.1%
Other values (4) 19
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 4619
15.3%
1 4420
14.6%
3 3882
12.9%
7 2963
9.8%
5 2831
9.4%
0 2637
8.7%
4 2625
8.7%
8 2341
7.7%
6 2096
6.9%
9 1795
 
5.9%
Space Separator
ValueCountFrequency (%)
224210
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3703
100.0%
Open Punctuation
ValueCountFrequency (%)
( 603
100.0%
Close Punctuation
ValueCountFrequency (%)
) 603
100.0%
Math Symbol
ValueCountFrequency (%)
+ 208
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1735549
84.9%
Common 309229
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 168937
 
9.7%
E 167836
 
9.7%
R 120881
 
7.0%
I 118880
 
6.8%
O 118820
 
6.8%
N 112975
 
6.5%
S 111772
 
6.4%
T 101530
 
5.9%
C 96556
 
5.6%
L 90466
 
5.2%
Other values (42) 526896
30.4%
Common
ValueCountFrequency (%)
224210
72.5%
' 16338
 
5.3%
. 9461
 
3.1%
& 8177
 
2.6%
, 6941
 
2.2%
# 5934
 
1.9%
2 4619
 
1.5%
1 4420
 
1.4%
3 3882
 
1.3%
- 3703
 
1.2%
Other values (22) 21544
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2044778
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
224210
 
11.0%
A 168937
 
8.3%
E 167836
 
8.2%
R 120881
 
5.9%
I 118880
 
5.8%
O 118820
 
5.8%
N 112975
 
5.5%
S 111772
 
5.5%
T 101530
 
5.0%
C 96556
 
4.7%
Other values (74) 702381
34.3%
Distinct22732
Distinct (%)21.0%
Missing662
Missing (%)0.6%
Memory size851.8 KiB
2024-02-15T22:30:59.247025image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length79
Median length46
Mean length17.778198
Min length2

Characters and Unicode

Total characters1926410
Distinct characters85
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6626 ?
Unique (%)6.1%

Sample

1st rowE Z MARKET, INC.
2nd rowJOHNNIE'S PIZZA
3rd rowDivan Chicago
4th rowSUBWAY
5th rowBurke
ValueCountFrequency (%)
9325
 
3.0%
restaurant 5249
 
1.7%
inc 4643
 
1.5%
the 4537
 
1.5%
food 4019
 
1.3%
cafe 3846
 
1.2%
grill 2902
 
0.9%
school 2893
 
0.9%
and 2779
 
0.9%
center 2605
 
0.8%
Other values (14905) 268689
86.3%
2024-02-15T22:31:00.234069image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
205181
 
10.7%
A 163854
 
8.5%
E 163069
 
8.5%
R 115833
 
6.0%
O 113506
 
5.9%
S 109040
 
5.7%
I 108388
 
5.6%
N 103587
 
5.4%
T 97690
 
5.1%
C 85397
 
4.4%
Other values (75) 660865
34.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1587848
82.4%
Space Separator 205181
 
10.7%
Lowercase Letter 66926
 
3.5%
Other Punctuation 40337
 
2.1%
Decimal Number 19076
 
1.0%
Dash Punctuation 3562
 
0.2%
Open Punctuation 1639
 
0.1%
Close Punctuation 1625
 
0.1%
Math Symbol 207
 
< 0.1%
Connector Punctuation 5
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8436
12.6%
a 6999
10.5%
o 5729
 
8.6%
n 5267
 
7.9%
r 5179
 
7.7%
i 4705
 
7.0%
l 4436
 
6.6%
t 4130
 
6.2%
s 3309
 
4.9%
c 2672
 
4.0%
Other values (17) 16064
24.0%
Uppercase Letter
ValueCountFrequency (%)
A 163854
 
10.3%
E 163069
 
10.3%
R 115833
 
7.3%
O 113506
 
7.1%
S 109040
 
6.9%
I 108388
 
6.8%
N 103587
 
6.5%
T 97690
 
6.2%
C 85397
 
5.4%
L 84045
 
5.3%
Other values (16) 443439
27.9%
Other Punctuation
ValueCountFrequency (%)
' 16710
41.4%
& 7854
19.5%
. 5625
 
13.9%
/ 3386
 
8.4%
# 3173
 
7.9%
, 3113
 
7.7%
@ 302
 
0.7%
! 128
 
0.3%
? 28
 
0.1%
: 10
 
< 0.1%
Other values (2) 8
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 3170
16.6%
2 3038
15.9%
3 2518
13.2%
7 2031
10.6%
5 1733
9.1%
4 1683
8.8%
0 1564
8.2%
6 1203
 
6.3%
8 1161
 
6.1%
9 975
 
5.1%
Open Punctuation
ValueCountFrequency (%)
( 1638
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1624
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
205181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3562
100.0%
Math Symbol
ValueCountFrequency (%)
+ 207
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1654774
85.9%
Common 271636
 
14.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 163854
 
9.9%
E 163069
 
9.9%
R 115833
 
7.0%
O 113506
 
6.9%
S 109040
 
6.6%
I 108388
 
6.6%
N 103587
 
6.3%
T 97690
 
5.9%
C 85397
 
5.2%
L 84045
 
5.1%
Other values (43) 510365
30.8%
Common
ValueCountFrequency (%)
205181
75.5%
' 16710
 
6.2%
& 7854
 
2.9%
. 5625
 
2.1%
- 3562
 
1.3%
/ 3386
 
1.2%
# 3173
 
1.2%
1 3170
 
1.2%
, 3113
 
1.1%
2 3038
 
1.1%
Other values (22) 16824
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1926405
> 99.9%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
205181
 
10.7%
A 163854
 
8.5%
E 163069
 
8.5%
R 115833
 
6.0%
O 113506
 
5.9%
S 109040
 
5.7%
I 108388
 
5.6%
N 103587
 
5.4%
T 97690
 
5.1%
C 85397
 
4.4%
Other values (74) 660860
34.3%
None
ValueCountFrequency (%)
ñ 5
100.0%

License #
Real number (ℝ)

Distinct31377
Distinct (%)28.8%
Missing7
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1957467.2
Minimum0
Maximum9999999
Zeros284
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size851.8 KiB
2024-02-15T22:31:00.581406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile22715
Q11716434
median2263388
Q32594751
95-th percentile2846208
Maximum9999999
Range9999999
Interquartile range (IQR)878317

Descriptive statistics

Standard deviation917542.97
Coefficient of variation (CV)0.4687399
Kurtosis0.29765273
Mean1957467.2
Median Absolute Deviation (MAD)368912
Skewness-1.1955034
Sum2.1338937 × 1011
Variance8.418851 × 1011
MonotonicityNot monotonic
2024-02-15T22:31:01.111025image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 284
 
0.3%
2594606 31
 
< 0.1%
22971 26
 
< 0.1%
2423912 26
 
< 0.1%
2510903 25
 
< 0.1%
1271546 25
 
< 0.1%
1042888 24
 
< 0.1%
1095992 23
 
< 0.1%
60184 23
 
< 0.1%
2738649 21
 
< 0.1%
Other values (31367) 108505
99.5%
ValueCountFrequency (%)
0 284
0.3%
2 3
 
< 0.1%
9 5
 
< 0.1%
40 4
 
< 0.1%
43 1
 
< 0.1%
62 4
 
< 0.1%
85 1
 
< 0.1%
104 1
 
< 0.1%
115 3
 
< 0.1%
139 1
 
< 0.1%
ValueCountFrequency (%)
9999999 1
< 0.1%
4076132 2
< 0.1%
4075924 2
< 0.1%
4075688 1
< 0.1%
4075628 2
< 0.1%
4075597 1
< 0.1%
4075446 1
< 0.1%
4075357 2
< 0.1%
4075346 1
< 0.1%
4075345 1
< 0.1%

Facility Type
Text

MISSING 

Distinct385
Distinct (%)0.4%
Missing1667
Missing (%)1.5%
Memory size851.8 KiB
2024-02-15T22:31:01.940993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length47
Median length10
Mean length11.251721
Min length3

Characters and Unicode

Total characters1207906
Distinct characters68
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)0.1%

Sample

1st rowGrocery Store
2nd rowRestaurant
3rd rowRestaurant
4th rowSchool
5th rowRestaurant
ValueCountFrequency (%)
restaurant 74081
50.5%
store 12332
 
8.4%
grocery 12245
 
8.4%
school 6958
 
4.7%
facility 3168
 
2.2%
services 3153
 
2.2%
daycare 3128
 
2.1%
children's 3120
 
2.1%
2 2877
 
2.0%
years 2874
 
2.0%
Other values (363) 22689
 
15.5%
2024-02-15T22:31:02.909494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 167079
13.8%
t 165646
13.7%
r 133020
11.0%
e 127275
10.5%
s 85024
7.0%
n 84366
7.0%
R 76183
 
6.3%
u 74661
 
6.2%
o 45726
 
3.8%
39276
 
3.3%
Other values (58) 209650
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 997991
82.6%
Uppercase Letter 158020
 
13.1%
Space Separator 39276
 
3.3%
Decimal Number 4947
 
0.4%
Other Punctuation 3453
 
0.3%
Open Punctuation 1462
 
0.1%
Close Punctuation 1462
 
0.1%
Dash Punctuation 1294
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 76183
48.2%
S 24212
 
15.3%
G 13083
 
8.3%
C 6278
 
4.0%
F 4432
 
2.8%
D 4095
 
2.6%
A 3620
 
2.3%
Y 3311
 
2.1%
T 3204
 
2.0%
U 2703
 
1.7%
Other values (16) 16899
 
10.7%
Lowercase Letter
ValueCountFrequency (%)
a 167079
16.7%
t 165646
16.6%
r 133020
13.3%
e 127275
12.8%
s 85024
8.5%
n 84366
8.5%
u 74661
7.5%
o 45726
 
4.6%
c 28880
 
2.9%
y 19986
 
2.0%
Other values (14) 66328
 
6.6%
Decimal Number
ValueCountFrequency (%)
2 2914
58.9%
6 1301
26.3%
1 249
 
5.0%
5 213
 
4.3%
8 206
 
4.2%
0 28
 
0.6%
3 27
 
0.5%
4 8
 
0.2%
7 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
' 3153
91.3%
/ 271
 
7.8%
& 18
 
0.5%
. 11
 
0.3%
Space Separator
ValueCountFrequency (%)
39276
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1462
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1462
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1294
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1156011
95.7%
Common 51895
 
4.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 167079
14.5%
t 165646
14.3%
r 133020
11.5%
e 127275
11.0%
s 85024
7.4%
n 84366
7.3%
R 76183
6.6%
u 74661
6.5%
o 45726
 
4.0%
c 28880
 
2.5%
Other values (40) 168151
14.5%
Common
ValueCountFrequency (%)
39276
75.7%
' 3153
 
6.1%
2 2914
 
5.6%
( 1462
 
2.8%
) 1462
 
2.8%
6 1301
 
2.5%
- 1294
 
2.5%
/ 271
 
0.5%
1 249
 
0.5%
5 213
 
0.4%
Other values (8) 300
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1207906
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 167079
13.8%
t 165646
13.7%
r 133020
11.0%
e 127275
10.5%
s 85024
7.0%
n 84366
7.0%
R 76183
 
6.3%
u 74661
 
6.2%
o 45726
 
3.8%
39276
 
3.3%
Other values (58) 209650
17.4%

Risk
Categorical

Distinct4
Distinct (%)< 0.1%
Missing39
Missing (%)< 0.1%
Memory size851.8 KiB
Risk 1 (High)
81922 
Risk 2 (Medium)
18819 
Risk 3 (Low)
8198 
All
 
42

Length

Max length15
Median length13
Mean length13.266285
Min length3

Characters and Unicode

Total characters1445773
Distinct characters23
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRisk 2 (Medium)
2nd rowRisk 2 (Medium)
3rd rowRisk 1 (High)
4th rowRisk 1 (High)
5th rowRisk 1 (High)

Common Values

ValueCountFrequency (%)
Risk 1 (High) 81922
75.1%
Risk 2 (Medium) 18819
 
17.3%
Risk 3 (Low) 8198
 
7.5%
All 42
 
< 0.1%
(Missing) 39
 
< 0.1%

Length

2024-02-15T22:31:03.221651image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-15T22:31:03.528055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
risk 108939
33.3%
1 81922
25.1%
high 81922
25.1%
2 18819
 
5.8%
medium 18819
 
5.8%
3 8198
 
2.5%
low 8198
 
2.5%
all 42
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
217878
15.1%
i 209680
14.5%
R 108939
7.5%
s 108939
7.5%
k 108939
7.5%
( 108939
7.5%
) 108939
7.5%
1 81922
 
5.7%
H 81922
 
5.7%
g 81922
 
5.7%
Other values (13) 227754
15.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 683158
47.3%
Uppercase Letter 217920
 
15.1%
Space Separator 217878
 
15.1%
Open Punctuation 108939
 
7.5%
Close Punctuation 108939
 
7.5%
Decimal Number 108939
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 209680
30.7%
s 108939
15.9%
k 108939
15.9%
g 81922
 
12.0%
h 81922
 
12.0%
d 18819
 
2.8%
m 18819
 
2.8%
u 18819
 
2.8%
e 18819
 
2.8%
o 8198
 
1.2%
Other values (2) 8282
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
R 108939
50.0%
H 81922
37.6%
M 18819
 
8.6%
L 8198
 
3.8%
A 42
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 81922
75.2%
2 18819
 
17.3%
3 8198
 
7.5%
Space Separator
ValueCountFrequency (%)
217878
100.0%
Open Punctuation
ValueCountFrequency (%)
( 108939
100.0%
Close Punctuation
ValueCountFrequency (%)
) 108939
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 901078
62.3%
Common 544695
37.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 209680
23.3%
R 108939
12.1%
s 108939
12.1%
k 108939
12.1%
H 81922
 
9.1%
g 81922
 
9.1%
h 81922
 
9.1%
d 18819
 
2.1%
m 18819
 
2.1%
u 18819
 
2.1%
Other values (7) 62358
 
6.9%
Common
ValueCountFrequency (%)
217878
40.0%
( 108939
20.0%
) 108939
20.0%
1 81922
 
15.0%
2 18819
 
3.5%
3 8198
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1445773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
217878
15.1%
i 209680
14.5%
R 108939
7.5%
s 108939
7.5%
k 108939
7.5%
( 108939
7.5%
) 108939
7.5%
1 81922
 
5.7%
H 81922
 
5.7%
g 81922
 
5.7%
Other values (13) 227754
15.8%
Distinct18062
Distinct (%)16.6%
Missing1
Missing (%)< 0.1%
Memory size851.8 KiB
2024-02-15T22:31:03.947089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length52
Median length40
Mean length18.618039
Min length1

Characters and Unicode

Total characters2029720
Distinct characters69
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4008 ?
Unique (%)3.7%

Sample

1st row6421 S DR MARTIN LUTHER KING JR DR
2nd row6558 S WESTERN AVE
3rd row868 N FRANKLIN ST
4th row1608 W 59TH ST
5th row5356 S DR MARTIN LUTHER KING JR DR
ValueCountFrequency (%)
ave 50189
 
11.4%
w 42910
 
9.7%
st 39756
 
9.0%
n 32864
 
7.4%
s 24343
 
5.5%
e 8859
 
2.0%
rd 6410
 
1.5%
clark 3867
 
0.9%
western 2766
 
0.6%
halsted 2657
 
0.6%
Other values (8105) 227016
51.4%
2024-02-15T22:31:04.967982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
440115
21.7%
E 123686
 
6.1%
A 117531
 
5.8%
S 100627
 
5.0%
N 85405
 
4.2%
T 83647
 
4.1%
1 82585
 
4.1%
0 67335
 
3.3%
R 65324
 
3.2%
W 63367
 
3.1%
Other values (59) 800098
39.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1048665
51.7%
Decimal Number 491243
24.2%
Space Separator 440115
21.7%
Lowercase Letter 33270
 
1.6%
Dash Punctuation 11563
 
0.6%
Close Punctuation 2186
 
0.1%
Open Punctuation 2186
 
0.1%
Other Punctuation 491
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 123686
11.8%
A 117531
11.2%
S 100627
 
9.6%
N 85405
 
8.1%
T 83647
 
8.0%
R 65324
 
6.2%
W 63367
 
6.0%
V 60374
 
5.8%
L 50557
 
4.8%
O 45848
 
4.4%
Other values (16) 252299
24.1%
Lowercase Letter
ValueCountFrequency (%)
a 3708
11.1%
e 3529
10.6%
t 3051
9.2%
n 2836
8.5%
r 2772
 
8.3%
o 2529
 
7.6%
i 2465
 
7.4%
l 2313
 
7.0%
h 1684
 
5.1%
s 1355
 
4.1%
Other values (14) 7028
21.1%
Decimal Number
ValueCountFrequency (%)
1 82585
16.8%
0 67335
13.7%
2 59815
12.2%
3 59617
12.1%
5 57077
11.6%
4 48972
10.0%
6 36294
7.4%
7 30628
 
6.2%
9 24478
 
5.0%
8 24442
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/ 276
56.2%
. 159
32.4%
& 47
 
9.6%
' 9
 
1.8%
Space Separator
ValueCountFrequency (%)
440115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11563
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2186
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2186
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1081935
53.3%
Common 947785
46.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 123686
11.4%
A 117531
10.9%
S 100627
 
9.3%
N 85405
 
7.9%
T 83647
 
7.7%
R 65324
 
6.0%
W 63367
 
5.9%
V 60374
 
5.6%
L 50557
 
4.7%
O 45848
 
4.2%
Other values (40) 285569
26.4%
Common
ValueCountFrequency (%)
440115
46.4%
1 82585
 
8.7%
0 67335
 
7.1%
2 59815
 
6.3%
3 59617
 
6.3%
5 57077
 
6.0%
4 48972
 
5.2%
6 36294
 
3.8%
7 30628
 
3.2%
9 24478
 
2.6%
Other values (9) 40869
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2029720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
440115
21.7%
E 123686
 
6.1%
A 117531
 
5.8%
S 100627
 
5.0%
N 85405
 
4.2%
T 83647
 
4.1%
1 82585
 
4.1%
0 67335
 
3.3%
R 65324
 
3.2%
W 63367
 
3.1%
Other values (59) 800098
39.4%

City
Text

Distinct62
Distinct (%)0.1%
Missing84
Missing (%)0.1%
Memory size851.8 KiB
2024-02-15T22:31:05.472421image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length19
Median length7
Mean length7.0038004
Min length5

Characters and Unicode

Total characters762966
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)< 0.1%

Sample

1st rowCHICAGO
2nd rowCHICAGO
3rd rowCHICAGO
4th rowCHICAGO
5th rowCHICAGO
ValueCountFrequency (%)
chicago 108777
99.8%
cchicago 20
 
< 0.1%
schaumburg 13
 
< 0.1%
park 12
 
< 0.1%
evanston 10
 
< 0.1%
maywood 10
 
< 0.1%
chicagochicago 9
 
< 0.1%
grove 9
 
< 0.1%
elk 8
 
< 0.1%
village 8
 
< 0.1%
Other values (60) 107
 
0.1%
2024-02-15T22:31:06.462445image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 217420
28.5%
A 108689
14.2%
O 108678
14.2%
I 108668
14.2%
H 108642
14.2%
G 108640
14.2%
c 299
 
< 0.1%
a 235
 
< 0.1%
o 235
 
< 0.1%
i 234
 
< 0.1%
Other values (32) 1226
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 761443
99.8%
Lowercase Letter 1465
 
0.2%
Space Separator 47
 
< 0.1%
Decimal Number 6
 
< 0.1%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 217420
28.6%
A 108689
14.3%
O 108678
14.3%
I 108668
14.3%
H 108642
14.3%
G 108640
14.3%
E 104
 
< 0.1%
L 84
 
< 0.1%
R 76
 
< 0.1%
N 66
 
< 0.1%
Other values (15) 376
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
c 299
20.4%
a 235
16.0%
o 235
16.0%
i 234
16.0%
g 233
15.9%
h 223
15.2%
y 1
 
0.1%
w 1
 
0.1%
d 1
 
0.1%
l 1
 
0.1%
Other values (2) 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
3 2
33.3%
1 2
33.3%
2 2
33.3%
Space Separator
ValueCountFrequency (%)
47
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 762908
> 99.9%
Common 58
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 217420
28.5%
A 108689
14.2%
O 108678
14.2%
I 108668
14.2%
H 108642
14.2%
G 108640
14.2%
c 299
 
< 0.1%
a 235
 
< 0.1%
o 235
 
< 0.1%
i 234
 
< 0.1%
Other values (27) 1168
 
0.2%
Common
ValueCountFrequency (%)
47
81.0%
. 5
 
8.6%
3 2
 
3.4%
1 2
 
3.4%
2 2
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 762966
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 217420
28.5%
A 108689
14.2%
O 108678
14.2%
I 108668
14.2%
H 108642
14.2%
G 108640
14.2%
c 299
 
< 0.1%
a 235
 
< 0.1%
o 235
 
< 0.1%
i 234
 
< 0.1%
Other values (32) 1226
 
0.2%

State
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)< 0.1%
Missing43
Missing (%)< 0.1%
Memory size851.8 KiB
IL
108966 
IN
 
7
CA
 
2
WI
 
1
NY
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters217954
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowIL
2nd rowIL
3rd rowIL
4th rowIL
5th rowIL

Common Values

ValueCountFrequency (%)
IL 108966
> 99.9%
IN 7
 
< 0.1%
CA 2
 
< 0.1%
WI 1
 
< 0.1%
NY 1
 
< 0.1%
(Missing) 43
 
< 0.1%

Length

2024-02-15T22:31:06.935124image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-15T22:31:07.353186image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
il 108966
> 99.9%
in 7
 
< 0.1%
ca 2
 
< 0.1%
wi 1
 
< 0.1%
ny 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
I 108974
50.0%
L 108966
50.0%
N 8
 
< 0.1%
C 2
 
< 0.1%
A 2
 
< 0.1%
W 1
 
< 0.1%
Y 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 217954
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 108974
50.0%
L 108966
50.0%
N 8
 
< 0.1%
C 2
 
< 0.1%
A 2
 
< 0.1%
W 1
 
< 0.1%
Y 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 217954
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 108974
50.0%
L 108966
50.0%
N 8
 
< 0.1%
C 2
 
< 0.1%
A 2
 
< 0.1%
W 1
 
< 0.1%
Y 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 217954
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 108974
50.0%
L 108966
50.0%
N 8
 
< 0.1%
C 2
 
< 0.1%
A 2
 
< 0.1%
W 1
 
< 0.1%
Y 1
 
< 0.1%

Zip
Real number (ℝ)

SKEWED 

Distinct108
Distinct (%)0.1%
Missing18
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean60628.02
Minimum10014
Maximum90504
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size851.8 KiB
2024-02-15T22:31:07.837332image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum10014
5-th percentile60605
Q160614
median60625
Q360643
95-th percentile60659
Maximum90504
Range80490
Interquartile range (IQR)29

Descriptive statistics

Standard deviation231.75877
Coefficient of variation (CV)0.0038226346
Kurtosis26713.735
Mean60628.02
Median Absolute Deviation (MAD)14
Skewness-72.305059
Sum6.6085755 × 109
Variance53712.126
MonotonicityNot monotonic
2024-02-15T22:31:08.368795image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60647 4119
 
3.8%
60614 3782
 
3.5%
60657 3698
 
3.4%
60608 3570
 
3.3%
60611 3442
 
3.2%
60618 3435
 
3.2%
60622 3270
 
3.0%
60607 3256
 
3.0%
60640 3054
 
2.8%
60625 3046
 
2.8%
Other values (98) 74330
68.2%
ValueCountFrequency (%)
10014 1
 
< 0.1%
46319 1
 
< 0.1%
46394 1
 
< 0.1%
46410 5
< 0.1%
53061 1
 
< 0.1%
60007 8
< 0.1%
60018 2
 
< 0.1%
60035 3
 
< 0.1%
60047 1
 
< 0.1%
60053 1
 
< 0.1%
ValueCountFrequency (%)
90504 1
 
< 0.1%
90067 1
 
< 0.1%
60827 104
 
0.1%
60805 2
 
< 0.1%
60804 2
 
< 0.1%
60714 3
 
< 0.1%
60707 628
0.6%
60706 3
 
< 0.1%
60666 1207
1.1%
60661 1413
1.3%
Distinct3477
Distinct (%)3.2%
Missing1
Missing (%)< 0.1%
Memory size851.8 KiB
Minimum2010-01-05 00:00:00
Maximum2024-02-08 00:00:00
2024-02-15T22:31:08.927590image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:31:09.450450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct53
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size851.8 KiB
2024-02-15T22:31:09.937763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length40
Median length7
Mean length10.872801
Min length3

Characters and Unicode

Total characters1185331
Distinct characters58
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)< 0.1%

Sample

1st rowCanvass
2nd rowComplaint
3rd rowLicense
4th rowCanvass Re-Inspection
5th rowCanvass
ValueCountFrequency (%)
canvass 66641
47.8%
re-inspection 23201
 
16.6%
license 21222
 
15.2%
complaint 17207
 
12.3%
non-inspection 2804
 
2.0%
short 2794
 
2.0%
form 2794
 
2.0%
suspected 329
 
0.2%
food 329
 
0.2%
poisoning 329
 
0.2%
Other values (56) 1704
 
1.2%
2024-02-15T22:31:10.691617image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 182081
15.4%
n 161800
13.7%
a 150999
12.7%
e 93638
7.9%
C 84057
 
7.1%
v 66715
 
5.6%
i 65906
 
5.6%
o 53902
 
4.5%
c 48311
 
4.1%
t 47273
 
4.0%
Other values (48) 230649
19.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 962891
81.2%
Uppercase Letter 165649
 
14.0%
Space Separator 30336
 
2.6%
Dash Punctuation 26165
 
2.2%
Decimal Number 273
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 84057
50.7%
I 26198
 
15.8%
R 23552
 
14.2%
L 21405
 
12.9%
F 3358
 
2.0%
S 3181
 
1.9%
N 2885
 
1.7%
P 345
 
0.2%
T 258
 
0.2%
O 124
 
0.1%
Other values (13) 286
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
s 182081
18.9%
n 161800
16.8%
a 150999
15.7%
e 93638
9.7%
v 66715
 
6.9%
i 65906
 
6.8%
o 53902
 
5.6%
c 48311
 
5.0%
t 47273
 
4.9%
p 43837
 
4.6%
Other values (12) 48429
 
5.0%
Decimal Number
ValueCountFrequency (%)
4 74
27.1%
1 70
25.6%
7 66
24.2%
5 58
21.2%
0 3
 
1.1%
8 2
 
0.7%
Other Punctuation
ValueCountFrequency (%)
/ 2
40.0%
. 2
40.0%
' 1
20.0%
Space Separator
ValueCountFrequency (%)
30336
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26165
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1128540
95.2%
Common 56791
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 182081
16.1%
n 161800
14.3%
a 150999
13.4%
e 93638
8.3%
C 84057
7.4%
v 66715
 
5.9%
i 65906
 
5.8%
o 53902
 
4.8%
c 48311
 
4.3%
t 47273
 
4.2%
Other values (35) 173858
15.4%
Common
ValueCountFrequency (%)
30336
53.4%
- 26165
46.1%
4 74
 
0.1%
1 70
 
0.1%
7 66
 
0.1%
5 58
 
0.1%
( 6
 
< 0.1%
) 6
 
< 0.1%
0 3
 
< 0.1%
8 2
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1185331
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 182081
15.4%
n 161800
13.7%
a 150999
12.7%
e 93638
7.9%
C 84057
 
7.1%
v 66715
 
5.6%
i 65906
 
5.6%
o 53902
 
4.5%
c 48311
 
4.1%
t 47273
 
4.0%
Other values (48) 230649
19.5%

Results
Categorical

Distinct7
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size851.8 KiB
Pass
47651 
Pass w/ Conditions
21866 
Fail
18303 
Out of Business
11617 
No Entry
6983 
Other values (2)
 
2599

Length

Max length20
Median length4
Mean length8.3595887
Min length4

Characters and Unicode

Total characters911354
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOut of Business
2nd rowNo Entry
3rd rowNot Ready
4th rowPass
5th rowPass

Common Values

ValueCountFrequency (%)
Pass 47651
43.7%
Pass w/ Conditions 21866
20.1%
Fail 18303
 
16.8%
Out of Business 11617
 
10.7%
No Entry 6983
 
6.4%
Not Ready 2559
 
2.3%
Business Not Located 40
 
< 0.1%
(Missing) 1
 
< 0.1%

Length

2024-02-15T22:31:11.020335image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-15T22:31:11.336162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
pass 69517
37.5%
w 21866
 
11.8%
conditions 21866
 
11.8%
fail 18303
 
9.9%
business 11657
 
6.3%
out 11617
 
6.3%
of 11617
 
6.3%
no 6983
 
3.8%
entry 6983
 
3.8%
not 2599
 
1.4%
Other values (2) 2599
 
1.4%

Most occurring characters

ValueCountFrequency (%)
s 195871
21.5%
a 90419
9.9%
76588
 
8.4%
i 73692
 
8.1%
P 69517
 
7.6%
o 64971
 
7.1%
n 62372
 
6.8%
t 43105
 
4.7%
d 24465
 
2.7%
u 23274
 
2.6%
Other values (16) 187080
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 660776
72.5%
Uppercase Letter 152124
 
16.7%
Space Separator 76588
 
8.4%
Other Punctuation 21866
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 195871
29.6%
a 90419
13.7%
i 73692
 
11.2%
o 64971
 
9.8%
n 62372
 
9.4%
t 43105
 
6.5%
d 24465
 
3.7%
u 23274
 
3.5%
w 21866
 
3.3%
l 18303
 
2.8%
Other values (5) 42438
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
P 69517
45.7%
C 21866
 
14.4%
F 18303
 
12.0%
B 11657
 
7.7%
O 11617
 
7.6%
N 9582
 
6.3%
E 6983
 
4.6%
R 2559
 
1.7%
L 40
 
< 0.1%
Space Separator
ValueCountFrequency (%)
76588
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 21866
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 812900
89.2%
Common 98454
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 195871
24.1%
a 90419
11.1%
i 73692
 
9.1%
P 69517
 
8.6%
o 64971
 
8.0%
n 62372
 
7.7%
t 43105
 
5.3%
d 24465
 
3.0%
u 23274
 
2.9%
w 21866
 
2.7%
Other values (14) 143348
17.6%
Common
ValueCountFrequency (%)
76588
77.8%
/ 21866
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 911354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 195871
21.5%
a 90419
9.9%
76588
 
8.4%
i 73692
 
8.1%
P 69517
 
7.6%
o 64971
 
7.1%
n 62372
 
6.8%
t 43105
 
4.7%
d 24465
 
2.7%
u 23274
 
2.6%
Other values (16) 187080
20.5%

Violations
Text

MISSING 

Distinct67922
Distinct (%)99.2%
Missing40526
Missing (%)37.2%
Memory size851.8 KiB
2024-02-15T22:31:11.930823image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10885
Median length4590
Mean length1169.4307
Min length30

Characters and Unicode

Total characters80098984
Distinct characters101
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67538 ?
Unique (%)98.6%

Sample

1st row57. ALL FOOD EMPLOYEES HAVE FOOD HANDLER TRAINING - Comments: 2-102.13 : OBSERVED NO FOOD HANDLERS TRAINING FOR ALL EMPLOYEES MUST PROVIDE AND MAINTAIN.
2nd row51. PLUMBING INSTALLED; PROPER BACKFLOW DEVICES - Comments: OBSERVED MISSING COLD WATER KNOB ON HANDWASHING SINK IN OLDER INFANTS ROOM. FACILITY HAS ABILITY TO TURN COLD WATER ON EVEN THOUGH KNOB IS MISSING. INSTRUCTED TO REPAIR OR REPLACE COLD WATER KNOB ON HANDWASHING SINK IN OLDER INFANTS ROOM.
3rd row38. INSECTS, RODENTS, & ANIMALS NOT PRESENT - Comments: OBSERVED REAR EXTERIOR DOORS LEADING TO PARKING LOT/DUMPSTER AREA TO HAVE 1/4 GAP AT BOTTOM. INSTRUCTED PERSON IN CHARGE TO REPAIR AND MAINTAIN FOR THE PREVENTION OF PEST ENTRY. | 52. SEWAGE & WASTE WATER PROPERLY DISPOSED - Comments: FACILTY UNABLE TO LOCATE GREASE TRAP FOR CONVEYANCE OF WASTE WATER FROM DISHMACHINE. INSTRUCTED PERSON IN CHARGE TO LOCATE OR INSTALL GREASE TRAP.
4th row57. ALL FOOD EMPLOYEES HAVE FOOD HANDLER TRAINING - Comments: 2-102.13 OBSERVED A FOOD HANDLING EMPLOYEE WITHOUT A VALID FOOD HANDLER CERTIFICATE. MANAGEMENT INSTRUCTED THAT ALL FOOD HANDLING EMPLOYEES MUST SHOW PROOF OF TRAINING.
5th row51. PLUMBING INSTALLED; PROPER BACKFLOW DEVICES - Comments: 5-204.12--BACKFLOW PREVENTION DEVICE NOT LOCATED AT COFFEE ESPRESSO MACHINE. MUST INSTALL SO BACKFLOW PREVENTION DEVICE MAY BE LOCATED TO BE SERVICED AND MAINTAINED. | 51. PLUMBING INSTALLED; PROPER BACKFLOW DEVICES - Comments: 5-205.15--OBSERVED WATER LEAK AT BASE OF FAUCET AT THE 3-COMPARTMENT SINK.INSTRUCTED TO REPAIR WATER PLUMBING LEAK AND MAINTAIN.
ValueCountFrequency (%)
736650
 
6.1%
and 464730
 
3.9%
comments 322436
 
2.7%
to 288826
 
2.4%
the 261783
 
2.2%
in 230942
 
1.9%
food 223257
 
1.9%
of 178259
 
1.5%
instructed 174764
 
1.5%
observed 164466
 
1.4%
Other values (80259) 8963615
74.6%
2024-02-15T22:31:13.192644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12146236
15.2%
E 6706430
 
8.4%
O 4900493
 
6.1%
N 4815721
 
6.0%
I 4811748
 
6.0%
A 4721682
 
5.9%
T 4607610
 
5.8%
R 4061819
 
5.1%
S 3592893
 
4.5%
D 3191308
 
4.0%
Other values (91) 26543044
33.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 57937296
72.3%
Space Separator 12146249
 
15.2%
Lowercase Letter 4786138
 
6.0%
Other Punctuation 2362066
 
2.9%
Decimal Number 1763585
 
2.2%
Dash Punctuation 704925
 
0.9%
Math Symbol 246844
 
0.3%
Open Punctuation 72360
 
0.1%
Close Punctuation 71635
 
0.1%
Currency Symbol 5145
 
< 0.1%
Other values (5) 2741
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 6706430
11.6%
O 4900493
 
8.5%
N 4815721
 
8.3%
I 4811748
 
8.3%
A 4721682
 
8.1%
T 4607610
 
8.0%
R 4061819
 
7.0%
S 3592893
 
6.2%
D 3191308
 
5.5%
L 2598723
 
4.5%
Other values (16) 13928869
24.0%
Lowercase Letter
ValueCountFrequency (%)
m 692212
14.5%
e 618989
12.9%
o 540866
11.3%
n 530044
11.1%
t 523584
10.9%
s 495541
10.4%
a 220043
 
4.6%
i 180611
 
3.8%
r 157829
 
3.3%
l 152972
 
3.2%
Other values (16) 673447
14.1%
Other Punctuation
ValueCountFrequency (%)
. 1150721
48.7%
, 447449
 
18.9%
: 406126
 
17.2%
& 157372
 
6.7%
/ 81748
 
3.5%
; 73887
 
3.1%
# 25240
 
1.1%
' 11451
 
0.5%
* 3886
 
0.2%
" 2292
 
0.1%
Other values (7) 1894
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 295409
16.8%
5 283646
16.1%
3 256524
14.5%
1 237285
13.5%
2 156170
8.9%
7 143345
8.1%
4 138293
7.8%
8 131467
7.5%
6 74015
 
4.2%
9 47431
 
2.7%
Math Symbol
ValueCountFrequency (%)
| 246742
> 99.9%
= 64
 
< 0.1%
+ 29
 
< 0.1%
> 8
 
< 0.1%
< 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 72298
99.9%
[ 60
 
0.1%
{ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 71588
99.9%
] 46
 
0.1%
} 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12146236
> 99.9%
  13
 
< 0.1%
Control
ValueCountFrequency (%)
2703
> 99.9%
 1
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
` 4
66.7%
^ 2
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 704925
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 5145
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 18
100.0%
Other Symbol
ValueCountFrequency (%)
° 9
100.0%
Other Letter
ValueCountFrequency (%)
º 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 62723438
78.3%
Common 17375546
 
21.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 6706430
 
10.7%
O 4900493
 
7.8%
N 4815721
 
7.7%
I 4811748
 
7.7%
A 4721682
 
7.5%
T 4607610
 
7.3%
R 4061819
 
6.5%
S 3592893
 
5.7%
D 3191308
 
5.1%
L 2598723
 
4.1%
Other values (43) 18715011
29.8%
Common
ValueCountFrequency (%)
12146236
69.9%
. 1150721
 
6.6%
- 704925
 
4.1%
, 447449
 
2.6%
: 406126
 
2.3%
0 295409
 
1.7%
5 283646
 
1.6%
3 256524
 
1.5%
| 246742
 
1.4%
1 237285
 
1.4%
Other values (38) 1200483
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80098946
> 99.9%
None 38
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12146236
15.2%
E 6706430
 
8.4%
O 4900493
 
6.1%
N 4815721
 
6.0%
I 4811748
 
6.0%
A 4721682
 
5.9%
T 4607610
 
5.8%
R 4061819
 
5.1%
S 3592893
 
4.5%
D 3191308
 
4.0%
Other values (86) 26543006
33.1%
None
ValueCountFrequency (%)
  13
34.2%
° 9
23.7%
¶ 7
18.4%
§ 5
 
13.2%
º 4
 
10.5%

Latitude
Real number (ℝ)

HIGH CORRELATION 

Distinct15843
Distinct (%)14.6%
Missing445
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean41.880527
Minimum41.64467
Maximum42.021064
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size851.8 KiB
2024-02-15T22:31:13.533325image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum41.64467
5-th percentile41.72676
Q141.834422
median41.891591
Q341.939372
95-th percentile41.99738
Maximum42.021064
Range0.37639412
Interquartile range (IQR)0.10495047

Descriptive statistics

Standard deviation0.080656113
Coefficient of variation (CV)0.0019258619
Kurtosis-0.33129913
Mean41.880527
Median Absolute Deviation (MAD)0.049444273
Skewness-0.59074374
Sum4547178.3
Variance0.0065054085
MonotonicityNot monotonic
2024-02-15T22:31:13.851720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.0085364 1184
 
1.1%
41.78932932 395
 
0.4%
41.85045102 384
 
0.4%
41.88418751 258
 
0.2%
41.88199434 214
 
0.2%
41.89209414 188
 
0.2%
41.88807428 161
 
0.1%
41.88743405 152
 
0.1%
41.8552817 129
 
0.1%
41.75466012 127
 
0.1%
Other values (15833) 105383
96.7%
(Missing) 445
 
0.4%
ValueCountFrequency (%)
41.64467013 5
< 0.1%
41.64566748 1
 
< 0.1%
41.64637082 2
 
< 0.1%
41.64655405 1
 
< 0.1%
41.64863829 5
< 0.1%
41.64868838 1
 
< 0.1%
41.64874251 2
 
< 0.1%
41.64881845 1
 
< 0.1%
41.64936399 7
< 0.1%
41.64940779 3
< 0.1%
ValueCountFrequency (%)
42.02106425 12
< 0.1%
42.02086075 7
< 0.1%
42.02080848 6
< 0.1%
42.02008731 2
 
< 0.1%
42.01986688 8
< 0.1%
42.01958216 7
< 0.1%
42.019494 1
 
< 0.1%
42.01949107 12
< 0.1%
42.01948985 5
< 0.1%
42.01947448 3
 
< 0.1%

Longitude
Real number (ℝ)

HIGH CORRELATION 

Distinct15843
Distinct (%)14.6%
Missing445
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean-87.675222
Minimum-87.914428
Maximum-87.525094
Zeros0
Zeros (%)0.0%
Negative108575
Negative (%)99.6%
Memory size851.8 KiB
2024-02-15T22:31:14.161892image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-87.914428
5-th percentile-87.776358
Q1-87.706059
median-87.665303
Q3-87.634686
95-th percentile-87.597958
Maximum-87.525094
Range0.3893343
Interquartile range (IQR)0.071373634

Descriptive statistics

Standard deviation0.057634269
Coefficient of variation (CV)-0.00065736097
Kurtosis2.3849904
Mean-87.675222
Median Absolute Deviation (MAD)0.03368083
Skewness-1.0070217
Sum-9519337.2
Variance0.0033217089
MonotonicityNot monotonic
2024-02-15T22:31:14.467671image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-87.91442844 1184
 
1.1%
-87.74164564 395
 
0.4%
-87.65879786 384
 
0.4%
-87.64111967 258
 
0.2%
-87.63975868 214
 
0.2%
-87.61156988 188
 
0.2%
-87.6349552 161
 
0.1%
-87.68184949 152
 
0.1%
-87.63199264 129
 
0.1%
-87.74138476 127
 
0.1%
Other values (15833) 105383
96.7%
(Missing) 445
 
0.4%
ValueCountFrequency (%)
-87.91442844 1184
1.1%
-87.91373767 1
 
< 0.1%
-87.90530913 11
 
< 0.1%
-87.88270766 2
 
< 0.1%
-87.86302998 8
 
< 0.1%
-87.84631989 6
 
< 0.1%
-87.84631558 2
 
< 0.1%
-87.8463105 1
 
< 0.1%
-87.84567442 7
 
< 0.1%
-87.8448585 10
 
< 0.1%
ValueCountFrequency (%)
-87.52509414 4
< 0.1%
-87.52512485 8
< 0.1%
-87.52571243 3
 
< 0.1%
-87.5258717 8
< 0.1%
-87.5261364 5
< 0.1%
-87.52664793 9
< 0.1%
-87.52667081 4
< 0.1%
-87.52694018 7
< 0.1%
-87.52749847 2
 
< 0.1%
-87.52797024 8
< 0.1%
Distinct15843
Distinct (%)14.6%
Missing445
Missing (%)0.4%
Memory size851.8 KiB
2024-02-15T22:31:14.962072image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length40
Median length39
Mean length39.060087
Min length34

Characters and Unicode

Total characters4240949
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2312 ?
Unique (%)2.1%

Sample

1st row(41.77776928832673, -87.615417280148)
2nd row(41.773871250304225, -87.68364377802502)
3rd row(41.898570078701034, -87.63590300760663)
4th row(41.786849792502515, -87.66480141216883)
5th row(41.79679284535837, -87.61617809193172)
ValueCountFrequency (%)
42.008536400868735 1184
 
0.5%
87.91442843927047 1184
 
0.5%
41.789329323265385 395
 
0.2%
87.74164564419637 395
 
0.2%
41.85045102427 384
 
0.2%
87.65879785567869 384
 
0.2%
41.884187507127805 258
 
0.1%
87.64111966683218 258
 
0.1%
41.88199433820508 214
 
0.1%
87.6397586848809 214
 
0.1%
Other values (31676) 212280
97.8%
2024-02-15T22:31:15.728181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 440565
10.4%
7 434391
10.2%
4 406789
9.6%
1 374973
8.8%
6 368291
8.7%
9 325295
7.7%
5 297708
 
7.0%
2 288567
 
6.8%
3 282977
 
6.7%
0 261368
 
6.2%
Other values (6) 760025
17.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3480924
82.1%
Other Punctuation 325725
 
7.7%
Open Punctuation 108575
 
2.6%
Space Separator 108575
 
2.6%
Dash Punctuation 108575
 
2.6%
Close Punctuation 108575
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 440565
12.7%
7 434391
12.5%
4 406789
11.7%
1 374973
10.8%
6 368291
10.6%
9 325295
9.3%
5 297708
8.6%
2 288567
8.3%
3 282977
8.1%
0 261368
7.5%
Other Punctuation
ValueCountFrequency (%)
. 217150
66.7%
, 108575
33.3%
Open Punctuation
ValueCountFrequency (%)
( 108575
100.0%
Space Separator
ValueCountFrequency (%)
108575
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 108575
100.0%
Close Punctuation
ValueCountFrequency (%)
) 108575
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4240949
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 440565
10.4%
7 434391
10.2%
4 406789
9.6%
1 374973
8.8%
6 368291
8.7%
9 325295
7.7%
5 297708
 
7.0%
2 288567
 
6.8%
3 282977
 
6.7%
0 261368
 
6.2%
Other values (6) 760025
17.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4240949
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 440565
10.4%
7 434391
10.2%
4 406789
9.6%
1 374973
8.8%
6 368291
8.7%
9 325295
7.7%
5 297708
 
7.0%
2 288567
 
6.8%
3 282977
 
6.7%
0 261368
 
6.2%
Other values (6) 760025
17.9%

Interactions

2024-02-15T22:30:50.578341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:43.784898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:45.160160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:46.802015image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:48.473586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:51.025346image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:44.062789image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:45.447837image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:47.083448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:48.904744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:51.469571image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:44.322368image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:45.721949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:47.362411image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:49.309962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:51.919458image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:44.610838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:46.007994image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:47.662849image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:49.691484image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:52.337959image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:44.884965image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:46.478544image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:48.009070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-15T22:30:50.141390image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-02-15T22:31:16.010650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Inspection IDLatitudeLicense #LongitudeResultsRiskStateZip
Inspection ID1.000-0.0090.316-0.0010.1420.0790.000-0.007
Latitude-0.0091.000-0.022-0.4090.0400.0501.0000.273
License #0.316-0.0221.0000.0290.0600.0290.000-0.023
Longitude-0.001-0.4090.0291.0000.0350.0451.000-0.405
Results0.1420.0400.0600.0351.0000.1110.000-0.013
Risk0.0790.0500.0290.0450.1111.0000.008-0.004
State0.0001.0000.0001.0000.0000.0081.000-0.017
Zip-0.0070.273-0.023-0.405-0.013-0.004-0.0171.000

Missing values

2024-02-15T22:30:53.381547image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-15T22:30:54.545982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-02-15T22:30:55.827084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Inspection IDDBA NameAKA NameLicense #Facility TypeRiskAddressCityStateZipInspection DateInspection TypeResultsViolationsLatitudeLongitudeLocation
02589380E Z MARKET, INC.E Z MARKET, INC.2570023.0Grocery StoreRisk 2 (Medium)6421 S DR MARTIN LUTHER KING JR DRCHICAGOIL60637.002/08/2024CanvassOut of BusinessNaN41.777769-87.615417(41.77776928832673, -87.615417280148)
12589355JOHNNIE'S PIZZAJOHNNIE'S PIZZA2929271.0RestaurantRisk 2 (Medium)6558 S WESTERN AVECHICAGOIL60636.002/08/2024ComplaintNo EntryNaN41.773871-87.683644(41.773871250304225, -87.68364377802502)
22589334Divan ChicagoDivan Chicago2943902.0NaNRisk 1 (High)868 N FRANKLIN STCHICAGOIL60610.002/08/2024LicenseNot ReadyNaN41.898570-87.635903(41.898570078701034, -87.63590300760663)
32589332SUBWAYSUBWAY2665377.0RestaurantRisk 1 (High)1608 W 59TH STCHICAGOIL60636.002/08/2024Canvass Re-InspectionPass57. ALL FOOD EMPLOYEES HAVE FOOD HANDLER TRAINING - Comments: 2-102.13 : OBSERVED NO FOOD HANDLERS TRAINING FOR ALL EMPLOYEES MUST PROVIDE AND MAINTAIN.41.786850-87.664801(41.786849792502515, -87.66480141216883)
42589341BurkeBurke22411.0SchoolRisk 1 (High)5356 S DR MARTIN LUTHER KING JR DRCHICAGOIL60615.002/08/2024CanvassPassNaN41.796793-87.616178(41.79679284535837, -87.61617809193172)
52589328MORITAS TACOS INC.MORITAS TACOS INC.2757311.0RestaurantRisk 1 (High)11436 S MICHIGAN AVECHICAGOIL60628.002/07/2024CanvassOut of BusinessNaN41.686017-87.620976(41.68601702970069, -87.62097609686657)
62589282CONTEMPORARY PRESCHOOL LLCCONTEMPORARY PRESCHOOL LLC2501524.0Children's Services FacilityRisk 1 (High)1400 N LAKE SHORE DRCHICAGOIL60610.002/07/2024LicensePass51. PLUMBING INSTALLED; PROPER BACKFLOW DEVICES - Comments: OBSERVED MISSING COLD WATER KNOB ON HANDWASHING SINK IN OLDER INFANTS ROOM. FACILITY HAS ABILITY TO TURN COLD WATER ON EVEN THOUGH KNOB IS MISSING. INSTRUCTED TO REPAIR OR REPLACE COLD WATER KNOB ON HANDWASHING SINK IN OLDER INFANTS ROOM.41.907909-87.625946(41.90790946673667, -87.62594577820322)
72589279LOS MANGOSLOS MANGOS2757143.0RestaurantRisk 1 (High)5923 W 63RD STCHICAGOIL60638.002/07/2024CanvassOut of BusinessNaN41.777782-87.769973(41.77778201293689, -87.76997257726937)
82589257LITTLE JOE'S CIRCLE LOUNGE INCLITTLE JOE'S CIRCLE LOUNGE INC319.0RestaurantRisk 1 (High)1041 W TAYLOR STCHICAGOIL60607.002/06/2024Non-InspectionNo EntryNaN41.869371-87.652781(41.86937117592203, -87.65278082182138)
92589255LA CATEDRAL EXPRESSLA CATEDRAL EXPRESS2951472.0RestaurantRisk 1 (High)4720 S CALIFORNIA AVECHICAGOIL60632.002/06/2024LicensePass38. INSECTS, RODENTS, & ANIMALS NOT PRESENT - Comments: OBSERVED REAR EXTERIOR DOORS LEADING TO PARKING LOT/DUMPSTER AREA TO HAVE 1/4 GAP AT BOTTOM. INSTRUCTED PERSON IN CHARGE TO REPAIR AND MAINTAIN FOR THE PREVENTION OF PEST ENTRY. | 52. SEWAGE & WASTE WATER PROPERLY DISPOSED - Comments: FACILTY UNABLE TO LOCATE GREASE TRAP FOR CONVEYANCE OF WASTE WATER FROM DISHMACHINE. INSTRUCTED PERSON IN CHARGE TO LOCATE OR INSTALL GREASE TRAP.41.807634-87.694334(41.80763360212086, -87.69433411628155)
Inspection IDDBA NameAKA NameLicense #Facility TypeRiskAddressCityStateZipInspection DateInspection TypeResultsViolationsLatitudeLongitudeLocation
1090102181228SIMPLY SOUPS SALADS & SANDWICHESSIMPLY SOUPS SALADS & SANDWICHES2222369.0RestaurantRisk 1 (High)635 E 47TH STCHICAGOIL60653.006/12/2018CanvassFail2. FACILITIES TO MAINTAIN PROPER TEMPERATURE - Comments: Observed Facility cold holding units not maintaining 40 degrees F or below. 2 door prep reach in cooler on north wall 49.1 degrees F, 2 door prep cooler on east wall 51.8 degrees F. Instructed person in charge to repair units and maintain proper cold holding temperatures of 40 degrees f or below. Tagged both units. CRITICAL VIOLATION 7-38-005A | 3. POTENTIALLY HAZARDOUS FOOD MEETS TEMPERATURE REQUIREMENT DURING STORAGE, PREPARATION DISPLAY AND SERVICE - Comments: Observed potentially hazardous food not meeting temperature requirements of 40 degrees F or below. cut tomato 55.4F, chicken 56.7F, hard boiled eggs 48.9, salmon 53.6 in prep cooler on east wall, cooked pork 48.9F, chicken 51.1F cooked salmon 52.0F, turkey 44.6F in 2 door prep reach in cooler on north wall, wedding soup 53.6F, in 2 door reach cooler on south wall. Person in charge voluntary discarded food items. CRITICAL VIOLATION 7-38-005A | 6. HANDS WASHED AND CLEANED, GOOD HYGIENIC PRACTICES; NO BARE HAND CONTACT WITH READY-TO-EAT FOODS. - Comments: Observed food handler utilized bare hand contact on ready to eat food, prepping sandwiches and handling clean cut leafy greens with bare hands. Food handler voluntary discarded food items contacted with bare hands. Critical Violation 7-38-010A | 29. PREVIOUS MINOR VIOLATION(S) CORRECTED 7-42-090 - Comments: Observed previous minor violation not corrected from previous inspection 2098652 performed on 10-12-17. #35 CLEAN WALL VENT ABOVE 3-COMPARTMENT SINK AND ALL CEILING VENTS(DUST BUILDUP). CLEAN WALLS BEHIND PANINI MACHINES. REPLACE STAINED CEIING TILES IN LOBBY. #43 STORE WASH CLOTHS IN SANITIZING SOLUTION AT THE REQUIRED PPM. #45 PROVIDE FOOD HANDLER TRAINING FOR ALL EMPLOYEES. Must repair, correct and maintain. Serious Violation 7-42-090 | 40. REFRIGERATION AND METAL STEM THERMOMETERS PROVIDED AND CONSPICUOUS - Comments: Prep cooler missing thermometers and conspicuous area. Must obtain and maintain.41.809372-87.610146(41.809372191240705, -87.61014589939184)
1090112159519SUBWAYSUBWAY1574489.0RestaurantRisk 1 (High)2300 N MILWAUKEE AVECHICAGOIL60647.004/05/2018Canvass Re-InspectionPass36. LIGHTING: REQUIRED MINIMUM FOOT-CANDLES OF LIGHT PROVIDED, FIXTURES SHIELDED - Comments: Found the rear closet with the water heater and mop sink in it to have no lighting. Instructed facility to install adequate lighting and to maintain.41.922843-87.697487(41.922842576706046, -87.69748748180638)
1090122169640THE BLACK FIRE BRIGADE ORG.THE BLACK FIRE BRIGADE ORG.2589092.0NOT-FOR-PROFIT CLUBRisk 2 (Medium)8404 S KEDZIE AVECHICAGOIL60652.005/11/2018License Re-InspectionPassNaN41.740484-87.702287(41.74048386093074, -87.70228691835008)
1090132169922LEAMINGTON FOODSLEAMINGTON FOODS36690.0Grocery StoreRisk 2 (Medium)5467 W MADISON STCHICAGOIL60644.005/17/2018Complaint Re-InspectionFail14. PREVIOUS SERIOUS VIOLATION CORRECTED, 7-42-090 - Comments: 14 - PREVIOUS SERIOUS VIOLATION FROM REPORT #2169372 ON 5/8/18 NOT CORRECTED: 29 - PREVIOUS MINOR VIOLATION FROM REPORT #2135983 ON 1/25/18 NOT CORRECTED: 38 - OBSERVED THE LEFT COMPARTMENT OF THE 3 COMPARTMENT SINK LEAKING WATER FROM THE SINK STOPPER LEVER. MANAGEMENT INSTRUCTED TO REPAIR THE LEAK. CRITICAL VIOLATION 7-42-090. | 35. WALLS, CEILINGS, ATTACHED EQUIPMENT CONSTRUCTED PER CODE: GOOD REPAIR, SURFACES CLEAN AND DUST-LESS CLEANING METHODS - Comments: REPLACE THE WATER STAINED CEILING TILES IN THE ROOM OUTSIDE OF THE MEAT WALK-IN COOLER AND ABOVE THE SALES FLOOR. | 36. LIGHTING: REQUIRED MINIMUM FOOT-CANDLES OF LIGHT PROVIDED, FIXTURES SHIELDED - Comments: REPLACE THE CRACKED LIGHT SHIELD IN THE MEAT CUTTING ROOM. REPLACE THE NON-WORKING LIGHTS IN THE MEAT CUTTING ROOM ABOVE THE 3 COMPARTMENT SINK. | 38. VENTILATION: ROOMS AND EQUIPMENT VENTED AS REQUIRED: PLUMBING: INSTALLED AND MAINTAINED - Comments: OBSERVED LOW HOT WATER PRESSURE AT THE EXPOSED HANDWASHING SINK AND 3 COMPARTMENT SINKS IN THE MEAT CUTTING ROOM. MUST PROVIDE ADDITIONAL WATER PRESSURE.41.880168-87.762539(41.88016817361682, -87.76253909209875)
1090142166494SI-PIESI-PIE2594598.0RestaurantRisk 1 (High)3349 N SHEFFIELD AVECHICAGOIL60657.004/23/2018License Re-InspectionPass35. WALLS, CEILINGS, ATTACHED EQUIPMENT CONSTRUCTED PER CODE: GOOD REPAIR, SURFACES CLEAN AND DUST-LESS CLEANING METHODS - Comments: FOUND WALLS AT MAIN KITCHEN WITH HOLES. MUST SEAL.41.943198-87.654060(41.943197684209125, -87.65405954840116)
1090152176368MO'S ASIAN BISTROMO'S ASIAN BISTRO2379500.0RestaurantRisk 1 (High)1353-1355 W FULLERTON AVECHICAGOIL60614.005/25/2018Canvass Re-InspectionPass30. FOOD IN ORIGINAL CONTAINER, PROPERLY LABELED: CUSTOMER ADVISORY POSTED AS NEEDED - Comments: OBSERVED READY TO EAT FOOD ITEMS NOT PROPERLY LABELED. MUST LABEL AND DATE ITEMS WITH THE PRODUCT NAME PREPARED BY DATE AND OR USUED BY DATE. MUST LABEL BULK FOOD STORAGE CONTAINERS IN REAR PREP AREA AND MUST MAINTAIN.41.925118-87.662634(41.92511824037609, -87.6626343537517)
1090162167055NEW HORIZON CENTER FOR DEVELOPMENT DISABLED CHILDRNEW HORIZON CENTER1981906.0SchoolRisk 1 (High)6737 W FOREST PRESERVE DRCHICAGOIL60634.005/02/2018CanvassPass w/ Conditions21. * CERTIFIED FOOD MANAGER ON SITE WHEN POTENTIALLY HAZARDOUS FOODS ARE PREPARED AND SERVED - Comments: FOUND NO CERTIFIED FOOD MANAGER ON SITE WHEN HANDLING POTENTIALLY HAZARDOUS FOODS (SANDWICHES, SOUPS, SALADS, CHICKEN, BEEF ETC). INSTRUCTED PERSON IN CHARGE, A CERTIFIED FOOD MANAGER WITH CITY OF CHICAGO FOOD SERVICE SANITATION MUST BE PRESENT WHEN HANDLING POTENTIALLY HAZARDOUS FOODS. SERIOUS VIOLATION 7-38-012 | 32. FOOD AND NON-FOOD CONTACT SURFACES PROPERLY DESIGNED, CONSTRUCTED AND MAINTAINED - Comments: INSTRUCTED TO PROVIDE SPLASH GUARD OR DIVIDER BETWEEN EXPOSED HAND SINK AND 3 COMPARTMENT SINK DRAIN BOARD IN PREP/COOKING AREA.---------MUST REPLACE CHIPPED ICE SCOOP (HANGING ON SIDE OF ICE MACHINE).--------- MUST SEAL OR PAINT RAW WOOD SHELVES IN REAR STORAGE (MAINTENANCE) ROOM. | 33. FOOD AND NON-FOOD CONTACT EQUIPMENT UTENSILS CLEAN, FREE OF ABRASIVE DETERGENTS - Comments: INSTRUCTED TO CLEAN AND MAINTAIN INTERIOR SURFACES OF REACH-IN FREEZER IN REAR MAINTENANCE STORAGE ROOM.-------MUST CLEAN DISH TRAY WITH DRIED FOOD DEBRIS ON SURFACES INSIDE STORAGE CABINETS IN DINING AREA. | 41. PREMISES MAINTAINED FREE OF LITTER, UNNECESSARY ARTICLES, CLEANING EQUIPMENT PROPERLY STORED - Comments: NOTED EMPLOYEE BELONGINGS STORED IN PREP/COOKING AREA. INSTRUCTED TO PROPERLY STORED INSIDE EMPLOYEE LOCKER ROOM.41.959415-87.795397(41.9594147126515, -87.7953974967148)
1090172181780BOJONOSBOJONOS PIZZERIA2594853.0RestaurantRisk 1 (High)4187-4189 N CLARENDON AVECHICAGOIL60613.006/21/2018LicensePassNaN41.958134-87.649657(41.95813411500559, -87.64965709096715)
1090182166643IRON LOTUSIRON LOTUS2589453.0RestaurantRisk 1 (High)1443-1445 W FULLERTON AVECHICAGOIL60614.004/24/2018LicensePassNaN41.925084-87.665044(41.925083972361364, -87.66504399327398)
1090192169351JIMMY JOHNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN